Plants and Light

Light as Source of Energy and Information

Pedro J. Aphalo

University of Helsinki and Natural Resources Institute Finland

2025-02-25

Plant-Light Interactions

flowchart LR
L((Light)) --> Ph[Photoreceptors<br/> _very low concentration_]
Ph --> In[Information] --> Rg[[Regulation<br/>photomorphogenesis]]
L --> Sc[Screening pigments<br/> _variable concentration_] 
Sc --> Ed[Energy dissipation] --> Pr[[Protection<br/>from damage]]
L --> Lh[Light-harvesting pigments<br/> _high concentration_] 
Lh --> Ps[Photosynthesis =<br/>Energy conversion] --> Gr[[Biomass<br/>plant growth]]

Tomato: Responses to the spectrum at equal photon irradiance.

Light Actions

Figure 1: Range of wavelengths sensed through different higher-plant photoreceptor families (black “information acquisition”) or driving photoreactions (orange “energy dependent”). DNA damage and repair, photosynthesis and photoreceptors; CRY: cryptochromes 1 and 2, PHOT: phototropins 1 and 2, ZTL: Zeitlupe, UVR8: “UV-B” photoreceptor, PHY: phytochromes A/B/C/D/E.

Light Screening and Absorption

Figure 2: Optical properties of leaves (green) and protective light-screening pigments (dark red). Thick lines indicate high absorption and paler narrower lines moderate absorption by pigments, or absorptance, reflectance or transmittance for whole leaves.

Energy flow: electricity to produce

flowchart TB
E(**Electricity**) ==> LED([LED + driver])
LED == 30 to 50% ==> L([Light<br/>_irradiance and spectrum_*])
LED -- 50 to 70% --> H[[Heat]]
L == 1 to 100% ==> IL[Intercepted by leaves<br/>_leaf area index or LAI by imaging_*]
L -- 100 to 1% --> NIL[Not intercepted by leaves<br/>_reaches soil, pots, shelves..._] 
NIL -- 100% --> WSA[Absorbed by objects] --> Hobj[[Heat]]
IL == 70 to 90% (LEDs) ===> Ab[Absorbed] 
IL -- 5 to 20% (LEDs) --> Rfl[[Reflected<br/>_imaging_*]]
IL -- 2 to 15% (LEDs) --> Tfr[[Transmitted<br/>_imaging?_*]]
Ab ==> Ph[Photosynthesis] == 2 to 5%<br/>of absorbed ==> Ch([Chemical energy<br/>_metabolites_])
Ab --> Fl[[Light<br/>_fluorescence_*]]
Ab --> He[Heat] --> Tleaf([_temperature of leaves_*])
Tleaf <--> Cv[[Convection<br/>_cooling or warming_]]
Tleaf --> Tr[[Transpiration<br/>_cooling_]]
Tr -- water use --> Sw([Soil water<br/>_pot weight_*]) 
Ch == 0 to 70% (?) ==> Gr[Growth<br/>_plant size and shape_*]
Ch -- 100 to 30% (?) --> Mn[[Maintenance<br/>_defence and repair_]]
Cv <--> Tair([Air temperature*])
Tr <--> Hair([Air water vapour*])
Tleaf <--> Thr[[Thermal radiation<br/>_cooling or warming_]]
Gr == ?% ==> Hv[[**Harvested**<br/>**produce**]]
Gr -- ?% --> Wst[[Waste]]

How does regulation affect growth rate?

  • Starting with a given amount of “building blocks” (sugars + minerals) decisions involve:
  • grow big roots and small shoots, or vice versa,
  • make large thin leaves or smaller thick leaves,
  • continue making only leaves, or start making “fruits”,
  • grow tall to avoid shade from neighbours or stay low and tolerate the shade.

The compromise

  • A larger surface of leaves intercepts more light driving a faster growth rate (similar to compound interest), but to a point.

  • Larger/longer roots have access to more water and minerals allowing building new leaves, so a balance is needed.

  • What is a good balance depends on light irradiance and soil conditions.

  • “Decisions by the plant” are based to a significant extent on the colour of light, because in nature the colour of light informs about future shade.

Sunlight

Figure 3: Time course of PAR photon irradiance during four consecutive days with different cloud conditions. Measured with broad band-sensors at Viikki, Helsinki, Finland.
Figure 4: Time series of scaled spectral photon irradiance during one day. Spectra scaled to \(Q_{\lambda 400..700 nm} = 1000 \mu mol\,s^{-1}\,m^{-2}\). Data from Andes Lindfors.

Plants’ shade

Figure 5: Light spectrum under a dense grove of young beech trees and in the open next to it.

LEDs for plant cultivation

Figure 6: Spectra of four contrasting LED grow lights.
Figure 7: Spectra of four contrasting LEDs sold for grow lights.